This article intends to justify the gap in the research of similarity coefficient driven approaches

and cell formation problems (CFP) based on ratio data in cellular manufacturing systems

(CMS). The actual implication of ratio data was vaguely addressed in past literature, which

has been corrected recently. This research considered that newly projected CFP based on

ration data. This study further revealed the lack of interest of researchers in investigation for

an appropriate and improved similarity coefficient primarily for CFP based on ratio data.

For that matter a novel similarity coefficient named as Generalized Utilization-based Similarity

Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter

a two-stage cell formation technique is adopted. First, the proposed GUSC based method

is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is

proposed to obtain effective part families. This proposed approach is successfully verified on

the test problems and compared with algorithms based on another similarity coefficient and

a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.

This paper presents the concept and methodology for the designing of a “tree-shaped” production line. The concept is a result of the search for production unit organization that meets the Lean Production assumptions, i.e. focusing on lead time (throughput time) shortening with simultaneous ability of use in conditions of varied product range. The varied product range characterized by lower technological-organizational similarity when compared to “Ushaped” units typical for Lean Production. The paper presents an algorithm for the designing of a “tree-shaped” production line and examples of its application. The designed unit underwent evaluation according to the criteria preferred by Lean Manufacturing experts. The designed production unit achieved results confirming the effectiveness of the proposed concept for the analysed sets of input data on the product range and production capacities.